Book Image

Hands-On Deep Learning for Images with TensorFlow

By : Will Ballard
Book Image

Hands-On Deep Learning for Images with TensorFlow

By: Will Ballard

Overview of this book

TensorFlow is Google’s popular offering for machine learning and deep learning, quickly becoming a favorite tool for performing fast, efficient, and accurate deep learning tasks. Hands-On Deep Learning for Images with TensorFlow shows you the practical implementations of real-world projects, teaching you how to leverage TensorFlow’s capabilities to perform efficient image processing using the power of deep learning. With the help of this book, you will get to grips with the different paradigms of performing deep learning such as deep neural nets and convolutional neural networks, followed by understanding how they can be implemented using TensorFlow. By the end of this book, you will have mastered all the concepts of deep learning and their implementation with TensorFlow and Keras.
Table of Contents (7 chapters)

Summary

Alright! We've learned about convolutions, which are a loosely connected way of moving over an image to extract features; we've learned about pooling, which summarizes the most important features; we've built a convolutional neural network using these techniques; and then finally, we combined many layers of convolution and pooling in order to generate a deep neural network.

In the next chapter, we're going to switch over to a bit more application development. We're going to be building an image classification REST server that can take different neural network models and serve those as APIs.